The chapters in this book explore the main domains that represent considerable risks for the respect of privacy, such as education, health, finance or social media. Through its place in the massive data production industry, the Internet of Things participates in the development of artificial intelligence and is increasingly attracting the attention of web giants, governments and especially all types of hackers. Thanks to this book, private and public organizations will have at their disposal a tool that highlights, on the one hand, the major challenges raised by privacy in the context of the Internet of Things and, on the other hand, recommendations for improving good practices. Digital identity is presented as a bulwark for the protection of privacy. It opens up new avenues for improving digital trust. Concretely, there are a set of challenges that are associated with the management of digital identity, mainly in relation to the compliance and governance of personnel data in order to eliminate privacy and security risks.

In today's rapidly evolving business landscape, organizations are inundated with vast amounts of data, making it increasingly challenging to extract meaningful insights and make informed decisions. The traditional business intelligence (BI) approach must often address the complexity and speed required for effective decision-making in this data-rich environment. As a result, many businesses need help to leverage their data to drive sustainable growth and remain competitive. Intersection of AI and Business Intelligence in Data-Driven Decision-Making presents a transformative solution to this pressing challenge. By exploring the convergence of artificial intelligence (AI) and BI, our book provides a comprehensive framework for leveraging AI-powered BI to revolutionize data analysis, predictive modeling, and decision-making processes. Readers will gain valuable insights into practical applications, emerging trends, and ethical considerations, inspiring and exciting them about the potential of AI in driving business success.

Marketing on digital platforms requires critical thinking on data management systems, machine learning methods, and attributes like customer trust, societal ethics, and managing consumer feedback with the utmost utilization of technology in different ways. The pursuit for a unified source of information is fundamental for marketers in digital marketing. Ethical Marketing Through Data Governance Standards and Effective Technology delves into the intricacies of achieving this unity by addressing the challenges and presenting solutions in a structured manner. The book explores the fundamental necessity for an effective data governance strategy. It emphasizes the eradication of silos and the establishment of regulations governing data classification, storage, and processing. Within this framework, the application of artificial intelligence in marketing takes center stage. The book investigates Artificial Intelligence (AI) marketing, machine learning methods, and data management systems. Furthermore, the book studies advertising standards and challenges on online platforms. The intersection of technology and advertising is dissected, focusing on virtual assistance through avatars and their impact on consumer psychology. The importance of a comprehensive database governance strategy is underscored, presenting a complete approach for corporations to navigate the intricacies of online marketing while upholding ethical standards.

Convergence of Blockchain, AI, and IoT: Concepts and Challenges discusses the convergence of three powerful technologies that play into the digital revolution and blur the lines between biological, digital, and physical objects. This book covers novel algorithms, solutions for addressing issues in applications, security, authentication, and privacy. The book provides an overview of the clinical scientific research enabling smart diagnosis equipment through AI. It presents the role these technologies play in augmented reality and blockchain, covers digital currency managed with bitcoin, and discusses deep learning and how it can enhance human thoughts and behaviors. Targeted audiences range from those interested in the technical revolution of blockchain, big data and the Internet of Things, to research scholars and the professional market.

This book covers the growing convergence between Blockchain and Artificial Intelligence for Big Data, Multi-Agent systems, the Internet of Things and 5G technologies. Using real case studies and project outcomes, it illustrates the intricate details of blockchain in these real-life scenarios. The contributions from this volume bring a state-of-the-art assessment of these rapidly evolving trends in a creative way and provide a key resource for all those involved in the study and practice of AI and Blockchain.

This book is devoted to the new standards, technologies, and communication systems for Artificial Intelligence of Things (AIoT) networks. Smart and intelligent communication networks have gained significant attention due to the combination of AI and IoT networks to improve human and machine interfaces and enhance data processing and services. AIoT networks involve the collection of data from several devices and sensor nodes in the environment. AI can enhance these networks to make them faster, greener, smarter, and safer. Computer vision, language processing, and speech recognition are some examples of AIoT networks. Due to a large number of devices in today’s world, efficient and intelligent data processing is essential for problem-solving and decision-making. AI multiplies the value of these networks and promotes intelligence and learning capabilities, especially in homes, offices, and cities. However, several challenges have been observed in deploying AIoT networks, such as scalability, complexity, accuracy, and robustness. In addition, these networks are integrated with cloud, 5G networks, and blockchain methods for service provision. Many different solutions have been proposed to address issues related to machine and deep learning methods, ontology-based approaches, genetic algorithms, and fuzzy-based systems. This book aims to contribute to the state of the art and present current standards, technologies, and approaches for AIoT networks. This book focuses on existing solutions in AIoT network technologies, applications, services, standards, architectures, and security provisions. This book also introduces some new architectures and models for AIoT networks.

Focusing on different tools, platforms, and techniques, Blockchain and the Smart City: Infrastructure and Implementation uses case studies from around the world to examine blockchain deployment in diverse smart city applications. The book begins by examining the fundamental theories and concepts of blockchain. It looks at key smart cities' domains such as banking, insurance, healthcare, and supply chain management. It examines Using case studies for each domain, the book looks at payment mechanisms, fog/edge computing, green computing, and algorithms and consensus mechanisms for smart cities implementation. It looks at tools such as Hyperledger, Etherium, Corda, IBM Blockchain, Hydrachain, as well as policies and regulatory standards, applications, solutions, and methodologies. While exploring future blockchain ecosystems for smart and sustainable city life, the book concludes with the research challenges and opportunities academics, researchers, and companies in implementing blockchain applications. - Independently organized chapters for greater readability, adaptability, and flexibility - Examines numerous issues from multiple perspectives and academic and industry experts - Explores both advances and challenges of cutting-edge technologies - Coverage of security, trust, and privacy issues in smart cities